1. Field
The present disclosure generally relates to a process for discovery, curation, adjudication and synthesis of complex dyadic and multiple counterparty global (that is, intra- and inter-jurisdictional and cross-border) business relationships. In particular, the disclosure relates to the creation of a system capable of discovering, qualifying, and recording dyadic and multi-counterparty relationships between business entities (hereinafter referred to as “business linkages”). The process comprises source-agnostic and non-deterministic analytic sub-processes which transform, measure, critically evaluate, adjudicate and refactor using clustering and affinity-recognition routines, which feed into self-improvement routines, so that the process and system functions as a highly recursive system that posits, tests, implements and monitors new strategies for the identification, confirmation, and maintenance of business linkages.
2. Discussion of the Background Art
The overall problem is to understand comprehensive relationships among business counter-parties. Typically, such understanding is applied to use cases involving total risk or total opportunity. Such understanding can also apply to more complex use cases, such as predictive analytics, remediation and scenario formulation.
Prior art for determination of the relationships, as exemplified in FIG. 6, attached hereto, include solutions which group entities having the same name together, but they are limited to use of only the name to trigger adjudication of the similarity and potential relationship. The technical problem is that such solutions do not provide effective automated and evolving curation capabilities and/or the ability to triangulate on a relationship by considering it from the perspective of multiple sources or indicia, some of which may be identified through analytic techniques. Also, such solutions typically either lack a manual curation and adjudication option, or perform their automated tasks with insufficient precision and accuracy to effectively filter potential relationships and ensure efficient use of the correct manual adjudication resources and processes. Without sufficient filtering or precision, potential relationships go through manual adjudication using a single “one size fits all” approach. The result is either a lack of reproducibility and difficulty driving economies of scale, for solutions with manual adjudication options, or for solutions without manual adjudication options, inconsistent, poor accuracy insufficient for all but the least critical business applications.
The technical effect of the present disclosure overcomes the disadvantages of conventional corporate linkage systems and processes by using a combination of (a) automated, recursive, and manual curation, (b) rules-based adjudication of sources and source combinations, and (c) multiple alternative indicia, to accurately determine the interrelationship context of business entities. Automated rules are leveraged against historical experiences and representative samples, results are thoroughly evaluated to determine “truth”, and rule improvement and tuning enables creation of a refined set of rules maximizing automation to enable scalability, while allowing for targeted and “most fitting” manual curation and adjudication strategies to be utilized as necessary.
Results assessment and tuning exploit detailed heuristic and analytic techniques, and include both established and emerging knowledge as well as learning algorithms and other approaches for adjudication of heterogeneous and highly dynamic, often unstructured data.
By supporting recursive testing and refinement of automation rules, and customization to optimize performance and minimize manual efforts, the present system maximizes effectiveness and the ability to leverage an increasing number of sources over time to widely expand scope without significantly increasing manual efforts, while continuing to accurately determine contextual relationships.
The present disclosure leverages logic to uniquely identify business entities through a robust identity resolution process, as a foundation upon which to evaluate context.
The present disclosure generates batch and transactional interactions, having either standardized, dynamic, and/or proprietary formats, enabling interaction with human resources who further adjudicate and evaluate the indicia to determine context.
The present disclosure also generates batch and transactional interactions, having either standardized, dynamic and/or proprietary formats, to synthesize updates and persist contextual insight.
Sources and processes are used to both establish and maintain contextual insight, by monitoring status, detecting active and passive change and initiating curation and adjudication as necessary.
The present disclosure precisely tracks results, and reporting tools are used to evaluate veracity and best-use of sources for tuning and diagnostic purposes, and self-learning features to improve performance based on experience. Reporting tools are also used to assess progress against known opportunities.
Manual discovery, curation and adjudication is performed by human resources having the best fit of experience and ability, based on complexity level, with rule based decisions routing to the resources.
The present disclosure also provides many additional advantages, which shall become apparent as described below.